An 8-step identity resolution process

In the world of customer data, things can get pretty complex. It’s commonplace for a single person's information to be scattered across different devices, accounts, products, and marketing efforts. 

For companies that want to offer personalized experiences, it's crucial to bring all this disparate data together—a unification only achieved through identity resolution.

Unfortunately, identity resolution is a highly complex process and tough to get right. But, help is at hand. 

This 8-step guide to identity resolution will help you successfully join the dots of (and unlock the value in) your customer data.

What is identity resolution?

Identity resolution connects user actions and attributes across multiple touchpoints and systems, giving you a complete view of how people interact as they move across devices and platforms. 

The primary goal of identity resolution is to link data (both online and offline) to customer profiles, so you can get a 360-degree view of their behavior. 

It’s the key to turning scattered pieces of customer information into something valuable for marketers, product managers, and sales teams.

Here’s how to implement identity resolution in your cloud data warehouse. 

An 8-step framework to implement identity resolution

1. Define your objectives

Before diving into the technical aspects of identity resolution, it's essential to identify your goals. 

What specific insights do you hope to gain from this process? Are you looking to improve personalization? To enhance data quality? Ensure privacy compliance? Bolster security? 

Clearly outlining your goals helps guide your implementation strategy.

2. Collect event data

The key data source you’ll be using is digital user data—such as event and user behavior data—that you collect from analytics tools like Contentsquare.

Begin by collecting this data and storing it in your cloud data warehouse. Ensure you capture relevant attributes, such as user IDs, device information, and timestamps.

3. Create identity graphs

Identity graphs are the foundation of identity resolution. These are tables that contain known customer identifiers and serve as a map to help you stitch together customer interactions. 

To create effective identity graphs in your cloud data warehouse, follow these steps:

• Pin-point key identifiers: determine crucial identifiers for linking customer interactions. These may be email addresses, phone numbers, account IDs, or user-generated IDs.

• Data transformation: use ETL (Extract, Transform, Load) processes to transform raw event data into structured tables that include these user identifiers.

• Map identifiers: create a structured mapping of how various identifiers relate to individual customers within your cloud data warehouse

4. Consolidate customer data

With event data and identity graphs in your cloud data warehouse, it's now time to consolidate customer data. 

This step involves linking and de-duplicating different customer actions. Here's how to proceed:

• Integrate: integrate data from various sources, including your event data and identity graphs, into a unified data repository in your cloud data warehouse

• Match identifiers: use your identity graphs to match customer identifiers across the different datasets in your cloud data warehouse, so you can link customer actions to specific profiles

• De-duplication: identify and eliminate duplicate records to keep data accurate

5. Link other entities to customer data

To build a 360-degree view of your customers, you need to link other entities, such as purchases or interactions, to individual customer profiles. 

Follow these steps in your cloud data warehouse:

1. Entity-relationship modeling: create an entity-relationship diagram (ERD) in your cloud data warehouse to visualize the relationships between users and the business entities you’re interested in

2. Data integration: integrate these entities into your customer data in your cloud data warehouse, ensuring they’re linked to the correct customer profiles

3. Attribute mapping: map attributes related to these entities to customer profiles within your cloud data warehouse for comprehensive insights

6. Implement deterministic and probabilistic methods

The source of your data plays a significant role in identity resolution, which is why the distinction between first-party and third-party data is crucial. 

• First-party data comes directly from your customers, and so provides a solid foundation for accurate identity resolution 

• Third-party data, by contrast, is obtained from vendors and is therefore less reliable when it comes to matching identities

There are 2 primary ways to match up data from these different sources.

Deterministic identity matching

Deterministic identity matching is a tried-and-true approach that primarily relies on first-party data, and works by gathering ‘known identifiers’ that other information is then attached to. 

For instance, when a user visits your website, they might initially receive an anonymous ID. If they later sign up or make a purchase, this anonymous ID gets linked to their email or user ID. 

Even when your user switches devices, deterministic matching can connect these IDs, forming an identity graph.

Probabilistic identity matching

By contrast, probabilistic matching uses non-deterministic data sources (such as data from third-party vendors) to make educated guesses about customer identities. 

This process considers factors like shared device usage, IP addresses, or fuzzy matching algorithms to piece together a user's identity.  

Companies like Liveramp and Identity are well-known in this field.

7. Use your new 360-degree customer view

Once you've successfully implemented identity resolution in your cloud data warehouse, you'll get a comprehensive 360-degree customer view. 

This newfound perspective opens the door to a multitude of valuable use cases, such as

• Personalized customer experiences (CX): tailor your product offerings, marketing messages, and user interfaces to individual customer behavior, preferences, and history

• Cross-channel engagement: identify users across devices and channels for effective omnichannel marketing campaigns. For instance, if a customer abandons a cart on their mobile device, you can retarget them with personalized offers on their desktop.

• Precision ad campaigns: suppress marketing to existing customers to avoid redundancy and focus your advertising efforts on acquiring new customers or re-engaging dormant ones

• Seamless online and offline integration: bridge the gap between online and offline customer experiences. For example, if a customer shops online but frequently visits your physical store, you can optimize marketing campaigns to send them physical coupons or in-store promotions.

• Enhanced analytics: leverage your 360-degree view to gain deeper insights into cross-channel and cross-device user behavior. This valuable data can drive more informed product decisions and marketing strategies.

• Fraud detection and prevention: identify and block fraudulent users more effectively by detecting unusual patterns of behavior within your enriched customer data

8. Test and refine your identity resolution process

Testing is a crucial aspect of implementation. 

Continuously monitor the accuracy and effectiveness of your identity resolution process within your cloud data warehouse—and adjust and refine your strategies to align with your objectives.

Embrace a data-driven culture that leverages the power of your cloud data warehouse to adapt and respond to changing customer needs.

Identity resolution is essential for great CX—but it’s not everything…

By implementing identity resolution in your cloud data warehouse, you empower your product managers and analysts to be agile and responsive to customer needs, while driving better product decisions and delivering superior customer experiences.

However, identity resolution isn’t enough to deliver amazing experiences that make your business stand out.

To achieve that, you need an experience intelligence platform that lets you

• Track your user behavior across multiple sessions and devices—on web, apps, and other branded experiences

• Leverage AI to surface insights into what’s engaging and frustrating users—without your team having to dig for them

• Dive into user behavior data with powerful investigative tools like Heatmaps and Session Replay

• Compare your CX against the competition in real time

There’s only one of those platforms out there—Contentsquare.